Research Scientist Graduate (Seed Model - Multimodal Interaction & World Model) - 2027 Start

About the team

The Seed Multimodal Interaction and World Model team is dedicated to developing models that have human-level multimodal understanding and interaction capabilities. The team is working to advance the exploration and development of multimodal assistant products.

We are looking for talented individuals to join our team. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth.

Successful candidates must be able to commit to an onboarding date by the end of the year. Please state your availability and graduation date clearly in your resume.

Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to our Company and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early.

Responsibilities

• Develop multimodal foundation models integrating vision, language, audio, and environment signals.
• Design and optimize world models for reasoning, planning, and interaction.
• Build training pipelines including data curation, alignment, and reinforcement learning.
• Improve agent capabilities such as perception, memory, decision-making, and tool use.
• Explore next-generation interaction paradigms between humans and intelligent systems.

Minimum Qualifications

• Individuals who are completing or have recently completed a BS degree in Computer Science, Electrical Engineering, Electrical and Computer Engineering, Physics, Mathematics, or a related discipline.
• Excellent coding ability, data structures, and fundamental algorithm skills, proficient in C/C++ or Python, etc.
• Demonstrated interest or project experience in relevant areas.

Preferred Qualifications

• Individuals who are completing or have recently completed a MS degree in Computer Science, Electrical Engineering, Electrical and Computer Engineering, Physics, Mathematics, or a related discipline.
• Experience in multimodal learning, reinforcement learning, or agent systems through internships is preferred.
• Strong problem-solving and collaboration skills.